Psychophysiological effects of music on acute recovery ...shura.shu.ac.uk/14610/1/Jones Psychophysiological effects of music on... · 2 Interval exercise has long been a staple of

Psychophysiological effects of music on acute recovery from high-intensity interval training

JONES, Leighton <http://orcid.org/0000-0002-7899-4119>, TILLER, Nicholas <http://orcid.org/0000-0001-8429-658X> and KARAGEORGHIS, Costas I.

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JONES, Leighton, TILLER, Nicholas and KARAGEORGHIS, Costas I. (2017). Psychophysiological effects of music on acute recovery from high-intensity interval training. Physiology & Behavior, 170, 106-114.

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Effects of music on acute recovery from HIIT 1

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Psychophysiological effects of music on acute recovery from high-intensity interval training 4

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Leighton Jones1, Nicholas B. Tiller

1, Costas I. Karageorghis

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1Academy of Sport and Physical Activity, Sheffield Hallam University, UK 9

2Department of Life Sciences, Brunel University London, UK 10

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Dr Nicholas B. Tiller, Sheffield Hallam University, Faculty of Health and Wellbeing, Collegiate Hall, 20

Collegiate Crescent, Sheffield S10 2BP, England, UK. 21

Tel: +44 (0)114 225 5962, Email: [email protected] 22

Dr Costas I. Karageorghis, Department of Life Sciences, Brunel University London, Uxbridge, 23

Middlesex UB8 3PH, England, UK 24

Tel: + 44 (0)1895 266 476, Fax: + 44 (0)1895 269 769, Email: [email protected] 25

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Correspondence concerning this article should be sent to: 28

Dr Leighton Jones, Sheffield Hallam University, Faculty of Health and Wellbeing, Collegiate Hall, 29

Collegiate Crescent, Sheffield S10 2BP, England, UK. 30

Tel: +44 (0)114 225 5590, Email: [email protected] 31

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mailto:[email protected]




Running head: Effects of music on acute recovery from HIIT 1

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Psychophysiological effects of music on acute recovery from high-intensity interval training 6

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Abstract 1

Numerous studies have examined the multifarious effects of music applied during exercise but few 2

have assessed the efficacy of music as an aid to recovery. Music might facilitate physiological 3

recovery via the entrainment of respiratory rhythms with music tempo. High-intensity exercise 4

training is not typically associated with positive affective responses, and thus ways of assuaging this 5

warrant further exploration. This study assessed the psychophysiological effects of music on acute 6

recovery and prevalence of entrainment in-between bouts of high-intensity exercise. Thirteen male 7

runners (Mage = 20.2 ± 1.9 years; BMI = 21.7 ± 1.7; V̇O2 max = 61.6 ± 6.1 ml·kg·min-1

) completed 8

three exercise sessions comprising 5 x 5-min bouts of high-intensity intervals interspersed with a 3-9

min passive recovery period. During recovery, participants were administered positively-valenced 10

music of a slow-tempo (55-65 bpm), fast-tempo (125-135 bpm), or a no-music control. A range of 11

measures including affective responses, RPE, cardiorespiratory indices (gas exchange and pulmonary 12

ventilation), and music tempo-respiratory entrainment were recorded during exercise and recovery. 13

Fast-tempo, positively-valenced music resulted in higher Feeling Scale scores throughout recovery 14

periods (p < .01, ηp2 = .38). There were significant differences in HR during initial recovery periods (p 15

< .05, ηp2 = .16), but no other music-moderated differences in cardiorespiratory responses. In 16

conclusion, fast-tempo, positively-valenced music applied during recovery periods engenders a more 17

pleasant experience. However, there is limited evidence that music expedites cardiorespiratory 18

recovery in-between bouts of high-intensity exercise. These findings have implications for athletic 19

training strategies and individuals seeking to make high-intensity exercise sessions more pleasant. 20

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Keywords: Affect; Entrainment; Exercise; HIIT; Tempo 22

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1. Introduction 1

A large body of literature has sought to delineate the ergogenic, psychological, and 2

psychophysical effects of music when applied pre-task or as an in-task accompaniment to exercise 3

(e.g., Eliakim et al., 2007; Hutchinson et al., 2011; Karageorghis & Jones, 2014). There is a paucity of 4

literature concerning the application of music as a post-task or recuperative aid, and further 5

exploration is required to elucidate its potential psychological and physiological benefits (Terry & 6

Karageorghis, 2011; Yamasaki et al., 2012). Among the few researchers who have assessed the 7

efficacy of music as a recuperative aid to exercise, Jing and Xudong (2008) explored the effects of 8

sedative music on passive recovery from a 15-min exhaustive cycle ergometer trial. In this instance, 9

sedative music led to decreases in heart rate (HR) intimating the capacity for sedative music to 10

expedite recovery from exercise. Contrastingly, applying motivational music post-exercise encourages 11

participants to engage in a more active recovery which, in turn, leads to reduced blood lactate 12

concentrations (Eliakim et al., 2012). 13

The emotional quality of music is a salient factor in promoting acute recovery from a stressor 14

and is a noteworthy consideration (see Karageorghis, 2016). Positively-valenced music that induces 15

low-levels of arousal has been shown to promote more effective physiological and subjective recovery 16

from psychological stress (Sandstrom, 2010). The tempo of a piece of music is a determinant of its 17

emotional qualities, with fast-tempo music consistently associated with states characterized by high-18

arousal and positive affective valence (e.g., Dalla Bella, Peretz, Rousseau, & Gosselin, 2001). Tempo 19

has also been shown to be one of the strongest correlates of physiological responses to music, with 20

fast-tempo music inducing higher breathing and heart rates (Gomez & Danuser, 2007). There is a 21

corpus of literature addressing the capacity of music to regulate emotions and, predominantly, humans 22

respond with positive emotions such as happiness and elation when listening to music (e.g., Juslin, 23

Liljestrom, Vastfjall, Barradas, & Silva, 2008). The findings of Juslin et al. (2008) indicate that 24

humans typically use music to promote positive emotional states, and the propensity for music to elicit 25

such positive states can be harnessed during exercise (Karageorghis, 2017). 26

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1.1 Exercise Intensity 1

Interval exercise has long been a staple of athletic training programs, and high-intensity 2

interval training (HIIT) is becoming increasingly popular among recreationally-active people owing to 3

its cardiovascular and metabolic benefits (e.g., Little et al., 2010). Sedative music might have a role to 4

play in facilitating cardiorespiratory recovery from high-intensity, intermittent exercise via several 5

neurogenic pathways. Animal models suggest that auditory stimulation with classical music directly 6

influences the autonomic nervous system via the gastric vagal nerve, resulting in elevated 7

parasympathetic function (Nakamura et al., 2009). Similarly, humans listening to relaxing music 8

exhibit increased parasympathetic drive, as assessed via heart rate variability (Perez-Lloret et al., 9

2014). Although not yet studied extensively in exercising individuals, auditory stimuli has been shown 10

to increase parasympathetic drive, leading to reductions in HR, respiration rate, and blood pressure, all 11

of which are key markers of cardiorespiratory recovery. It is possible that musical selections 12

characterized by a slow tempo may elicit similar responses in athletic populations. 13

In addition to physiological responses to high-intensity exercise, there is evidence to suggest 14

that incremental exercise from low-to-severe intensities causes in-task affective responses to shift from 15

a neutral or positive valence toward a negative valence (e.g., Smith et al., 2015). This shift was 16

conceptualized in the dual-mode model of exercise-related affect (Ekkekakis, 2003) and is a 17

consequence of the continuous interplay between cognitive processes and interoceptive cues (see e.g., 18

Acevedo & Ekkekakis, 2006, pp. 96–104). Although affective valence typically returns to pre-exercise 19

levels following vigorous activity (the so-called “affective rebound”; Ekkekakis, Hall, & Petruzzello, 20

2008), this phenomenon requires further examination in relation to HIIT, which is characterized by 21

repetitive exercise and multiple rest periods. High-intensity exercise sessions pose a challenge 22

regarding how the decline in affect might be assuaged. Given the increased adoption of HIIT by the 23

general population and that a lack of enjoyment is often cited as a barrier to exercise adherence 24

(Salmon et al., 2003), the affective responses to such exercise are a salient public health issue. There is 25

evidence to support the ergogenic and affect-enhancing benefits of self-selected music across the 26

entire course (during exercise and recovery periods) of a high-intensity interval training session (Stork 27

et al., 2015). Self-selected music, however, is generally unsuitable for studies that seek to examine 28


responses to specific qualities of music (e.g., tempo) owing to the wide variety of music that 1

participants will invariably select (see e.g., Hallett & Lamont, 2016). Moreover, the psycho-acoustic 2

qualities of music tracks vary greatly, which means that a nonstandardized approach poses a threat to 3

the internal validity of studies that examine the mechanisms underlying the efficacy of music. 4

1.2 Potential Underlying Mechanisms 5

The bio-musicological principle of entrainment pertains to a mechanism that underlies the 6

influence of music on physiological responses. Entrainment theory (Thaut, 2008, pp. 39-59) seeks to 7

explain how music influences the body’s main pulses such as brainwaves, HR, and respiratory rate 8

(e.g., Khalfa et al., 2008), and has been attributed, at least in part, to a central “pattern generator” or 9

pacemaker in the brain that serves to regulate temporal functioning (e.g., Schneider et al., 2010). In 12 10

participants, Haas et al. (1986) observed tight entrainment between music rhythm and respiratory duty 11

cycle (inspiration to expiration time), which was reinforced by rhythmic foot tapping. Furthermore, 12

Bernadi et al. (2005) reported a linear relationship between music tempi (ranging from 55–150 b.min

-1) 13

and two respiration indices (frequency and minute ventilation). This is of particular relevance to post-14

exercise recovery given that manipulation of breath movement resulting in an extension of respiratory 15

duty cycle (via deep, slow breathing) has been shown to lower blood pressure and peripheral 16

sympathetic nerve activity (Oneda, Ortega, Gusmao, Arauio, & Mion, 2010). Accordingly, it is 17

plausible that a music-modulated lowering of respiratory rate via the biomusicological principle of 18

entrainment might facilitate cardiorespiratory recovery from strenuous exercise. Of the components 19

that constitute a musical work, it is suggested that tempo is the most salient in promoting entrainment 20

(Khalfa et al., 2008; Thaut, 2008), and further exploration is required to examine the possible role of 21

this constituent of music in promoting post-exercise recovery. 22

The entrainment research conducted to date has focused predominantly upon resting 23

participants. If such entrainment between bodily rhythms and music can be replicated during the 24

recovery periods of high-intensity exercise, there could be a beneficial influence on the recovery of 25

cardiorespiratory variables by lowering respiratory frequency, and thus HR, to a rate that is determined 26

by the musical beat. This would, in turn, enhance exercise capacity by increasing cardiac reserve for 27


subsequent efforts. Similarly, it may be that starting high-intensity intervals from an enhanced 1

affective state limits the degree of displeasure experienced. 2

1.3 Study Aims 3

Despite a logical premise and plausible mechanistic foundation, few studies have assessed the 4

influence of music on acute psychological and cardiorespiratory recovery in-between bouts of high-5

intensity exercise. This study seeks to complement the contemporary theoretical models addressing the 6

use of music in exercise (e.g., Karageorghis, 2016), as well as inform athletic training programs. It was 7

hypothesized that slow-tempo, positively-valenced music applied in-between bouts of high-intensity 8

exercise would promote a more positive psychological state and facilitate acute cardiorespiratory 9

recovery when compared to fast-tempo, positively-valenced music and a no-music control. 10

2. Method 11

2.1. Stage 1: Music Selection 12

Twenty four music tracks were initially selected by the experimenters based on the tempo 13

ranges required to address the research question (12 slow-tempo: 55-65 bpm; 12 fast-tempo: 125-135 14

bpm). Tracks included in this selection had readily discernible beats that matched the published tempo. 15

Owing to difficulty in identifying suitable tracks in the range of 55-65 bpm, those at a tempo of ± 3 16

bpm were considered and digitally altered if appropriate. Previous empirical work indicates that tempo 17

changes of ± 4 bpm are indiscernible among nonmusicians (Levitin & Cook, 1996). 18

Eight participants (Mage = 25.2 ± 3.6 years) rated the 24 music tracks (3 min excerpts) with the 19

aim of identifying those suitable for use in the experimental protocol (Stage 2). Participants at each 20

stage of the study were similar in terms of age (18–30 years), and socio-cultural background (had 21

spent their formative years in the UK). Participants who reported any form of hearing deficiency or 22

congenital amusia (i.e., tone-deafness) were excluded. The 24 musical excerpts were rated using the 23

Affect Grid (Russell et al., 1989), providing two scores in line with each of its two dimensions: 24

pleasure–displeasure and low arousal–high arousal. Five slow-tempo tracks that were rated in the 25

bottom-right quadrant of the Affect Grid (i.e., “pleasant low-arousal”), and within one whole unit of 26

each other in terms of affective valence and arousal scores, were selected for use in the experimental 27

trials (see Table 1). Five fast-tempo tracks that were rated in the upper-right quadrant of the Affect 28


Grid (i.e., “pleasant high-arousal”) and within one whole unit of each other were selected for use in 1

Stage 2 (see Table 1). The affective valence (pleasure–displeasure) ratings of the slow- and fast-tempo 2

tracks were within one whole unit of each other, and the arousal scores for the fast-tempo tracks were 3

~4 units higher than those for the slow-tempo tracks. 4

2.2. Stage 2: Experimental Investigation 5

2.2.1. Power analysis. To establish appropriate sample size, a power analysis was undertaken 6

using the software G*Power3 (Faul et al., 2007). Based on a more conservative effect size than that of 7

Stork et al. (2015; ηp2 = .06), an alpha level of .05, and power at .8 to protect beta at four times the 8

level of alpha (Cohen, 1988, pp. 4–6), the analysis indicated that 12 participants would be required to 9

detect effects on affective responses (Feeling Scale). 10

2.2.2. Participants. Twenty well-trained, male middle-distance runners were initially 11

recruited for the experimental investigation, however, seven of these failed to complete all sessions 12

owing to injury, competitive commitments, or inability to sustain the required work rate. Therefore, 13 13

participants completed all experimental conditions (Mage = 20.2 ± 1.9 years; BMI = 21.7 ± 1.7). 14

Experimental procedures were approved by the ____ Research Ethics Committee and participants 15

provided written informed consent. Participants were asked to abstain from exercise for 24 h, alcohol 16

and caffeine for 12 h, and food for 3 h prior to each visit. Participants were similar in terms of training 17

status and maximal aerobic capacity (see Table 2). 18

2.2.3. Apparatus and measures. Participants exercised on a treadmill (HP Cosmos Saturn) 19

while cardiorespiratory data were collected on a breath-by-breath basis using an online gas analyzer 20

(Oxycon Pro), and HR monitored via telemetry (Vantage NV). Music was played from a laptop 21

computer connected to over-ear headphones (Sennheiser HD201) at a standardized sound intensity (75 22

dBA). Pre- and post-exercise blood samples were collected into a 10 µl capillary tube and 23

subsequently analyzed for blood lactate concentration (Biosen). Rating of perceived exertion (RPE) 24

was recorded using the Borg CR10 scale (Borg, 1998). Affective valence and arousal were assessed 25

using the Feeling Scale (FS; Hardy & Rejeski, 1989) and the Felt Arousal Scale (FAS; Svebak & 26

Murgatroyd, 1985), respectively. Van Landuyt et al. (2000) found the FS to be correlated (0.51–0.88) 27

with the valence scale of the Self-Assessment Manikin and with the Affect Grid (0.41–0.59). 28


Ekkekakis (2013) suggested that the tandem use of the FS and FAS strengthened the discriminant 1

validity of the scales. 2

2.2.4. Tempo-respiratory entrainment. Music tempo and respiratory rhythms were 3

considered to be matched when the instantaneous ratio of tempo to mean respiratory frequency, 4

recorded at 15 s intervals, was within ± 0.05 of a whole- or half-integer value (see Paterson et al., 5

1986). The prevalence of tempo-respiratory entrainment (ENT%) was calculated as the percentage of 6

the sampled data within each 3-min recovery period that met these criteria. The first and last 15 s of 7

each 3-min block were excluded from the analysis to account for the stabilization of respiratory 8

pattern and the recording of perceptual responses, respectively. 9

2.2.5. Maximal exercise test and habituation. Participants completed a maximal ramp 10

incremental exercise test on a motorized treadmill. Exercise commenced at 10 km.hr

-1 for 4 min at a 11

1% incline (warm-up) after which the speed was increased by 1 km.hr

-1 each minute until volitional 12

fatigue was reached. The test was designed to elicit maximal capacities within 8–12 min. Gas 13

exchange and HR were assessed continuously. Maximal aerobic capacity was deemed to have been 14

reached following the attainment of a single primary (plateau in oxygen uptake following an increase 15

in exercise intensity) or two secondary criteria (final RER ≥ 1.15, and HR within 10 bpm of age-16

predicted maximum) in accord with BASES Guidelines (Winter et al., 2006). Following the test, gas 17

exchange threshold (GET) was identified using multiple parallel methods (Wasserman, 1984). 18

Subsequent to the maximal exercise test, participants were familiarized with the experimental protocol 19

and measures. 20

2.2.6. Experimental protocol. Participants completed three exercise sessions separated by a 21

minimum of 2 days and a maximum of 7 days. Each session comprised a 4-min period of seated rest, 22

followed by a 4-min warm-up at a treadmill speed equivalent to 80% GET. Participants then 23

completed 5 x 5-min bouts of treadmill running at a speed equivalent to 20% of the difference between 24

GET and V̇O2 max (“heavy” exercise; Lansley et al., 2011), interspersed with 3-min periods of 25

standing recovery on the treadmill. A passive, standing recovery was selected to remove the potential 26

influence of locomotor–respiratory coupling that could manifest during an active (walking) recovery 27

period (Daley et al., 2013); such coupling might have confounded the assessment of tempo–respiratory 28


entrainment. During the standing recovery periods of a given session, participants were administered 1

one of the following conditions: slow-tempo music; fast-tempo music; or no-music (control). To 2

ensure parity of experience across conditions, headphones were worn during the control condition. 3

The order of conditions was randomized and exercise bouts were completed individually at the same 4

time of day to account for circadian variance. 5

The FS (Hardy & Rejeski, 1989) and FAS (Svebak & Murgatroyd, 1985) were administered 6

immediately prior to the warm-up. Rating of perceived exertion (Borg, 1998) was assessed in the final 7

10 s of each exercise bout. At the end of each bout, the participant straddled the treadmill belt and 8

headphones were placed over his ears. The music tracks had a 1-s fade-in and fade-out to avoid the 9

startle effect (Sandstrom, 2010). Gas exchange and ventilatory function were recorded continuously 10

throughout the aforementioned procedures; HR was recorded at the end of each bout and at the end of 11

each recovery period. The FS and FAS were administered 10 s before the end of the 3-min recovery 12

period. Thereafter, the participant resumed treadmill running. Blood lactate concentration was sampled 13

at resting baseline and immediately following the final music intervention using a 10 µl earlobe 14

capillary sample (Biosen). 15

2.3. Data Analysis 16

Following checks to ensure that the data were suitable for parametric analysis, a series of 17

MANOVAs and ANOVAs were applied. A 3 (condition) x 6 (time) MANOVA was used to analyze 18

responses to the Feeling Scale and Felt Arousal Scale; this analysis incorporated the baseline 19

responses. A series of 3 (condition) x 5 (time) ANOVAs were computed for the following dependent 20

variables: RPE, lowest HR during recovery period, mean breathing frequency during recovery (fR), O2 21

uptake during recovery (V̇O2), minute ventilation (V̇E) and mean Tidal Volume (VT) throughout the 22

recovery periods, and respiratory duty cycle (TTOT) during recovery. A series of 3 (condition) x 4 23

(time) ANOVAs was applied to HR (peak) and respiration measures collected during exercise (V̇O2, 24

V̇E, VT, and TTOT). The four exercise periods following the initial recovery period were included in 25

these analyses to explore the effects of the intervention, which only become relevant from the second 26

exercise bout. A 3 (condition) x 2 (time) ANOVA was applied for pre- and post-exercise blood lactate 27


values. The amount of time respiration rate was entrained with music tempo was analyzed using a 2 1

(condition) x 5 (time) ANOVA. 2

3. Results 3

Data screening revealed no univariate (z < ±3.29) or multivariate outliers (p < .001). Tests of 4

the distributional properties of the data in each cell of the analysis revealed 59 violations (z > ±1.96). 5

Specifically, the data for HR at the end of the recovery period and TTOT during exercise and recovery 6

exhibited positive skewness; therefore, a logarithmic transformation (log10) was applied to normalize 7

these data. Mauchly’s test indicated 21 instances in which the sphericity assumption had been 8

violated; therefore appropriate adjustments were applied to the relevant F tests. Descriptive statistics 9

for exercise bouts are presented in Table 3 and for recovery periods in Table 4. 10

3.1. Affective Responses 11

RM MANOVA for affective responses (Feeling Scale and Felt Arousal Scale; Table 4) 12

indicated no interaction effects (Pillai's Trace = .167, F[20, 240] = 1.10, p = .357, ηp2 = .08). However, 13

there was a significant effect of condition (Pillai's Trace = .425, F[4, 48] = 3.24, p = .020, ηp2 = .21) 14

and time (Pillai’s Trace = .438, F[10, 120] = 3.36, p = .001, ηp2 = .22). Step-down F tests are presented 15

for each measure. 16

3.1.1. Feeling Scale (FS). The main effect of condition was significant, F(1.37, 16.39) = 7.38, 17

p = .010, ηp2 = .38 with follow-up pairwise comparisons indicated that the fast-tempo music condition 18

was rated as significantly more pleasant than the no-music control (95% CI [1.31, .44], p = .000; see 19

Figure 1 and Table 4). The main effect of time was nonsignificant, F(2.01, 24.12) = .22, p = .803, ηp2 20

= .02. 21

3.1.2. Felt Arousal Scale (FAS). There was no main effect of condition, F(2, 24) = 1.16, p = 22

.330, ηp2 = .09. The main effect of time was significant, F(2.20, 26.41) = 5.87, p = .006, ηp

2 = .33, with 23

follow-up pairwise comparisons indicating that all recovery bouts resulted in higher levels of arousal 24

compared to baseline. 25

3.2. Psychophysical Response 26

3.2.1. Rating of Perceived Exertion (RPE). There was no condition x time interaction, F(8, 27

96) = 1.72, p = .103, ηp2 = .13, and the main effect of condition was also nonsignificant, F(2, 24) = .67, 28


p = .523, ηp2 = .05. There was a main effect of time, F(1.28, 15.40) = 13.79, p = .001, ηp

2 = .54, with 1

follow-up pairwise comparisons indicating that levels of exertion were elevated in the final three 2

exercise bouts when compared to the initial two exercise bouts (p < .05; Table 3). 3

3.3. Cardiorespiratory Responses 4

A series of significant main effects of time were revealed in analyses of HR, V̇E, VT, fR, and 5

TTOT during exercise bouts and recovery periods with data indicating increased stress as the exercise 6

session progressed (p < .01). 7

3.3.1. Heart rate during exercise. Analysis revealed no condition x time interaction, F(8, 88) 8

= .32, p = .958, ηp2 = .03, and no main effect of condition, F(2, 22) = .03, p = .972, ηp

2 = .01 (Table 3). 9

3.3.2. Heart rate during recovery. Analysis indicated a significant condition x time 10

interaction, F(8, 96) = 2.12, p = .034, ηp2 = .16, which was associated with a large effect. Inspection of 11

the means and standard errors indicated that HR was lower during the control condition in Recovery 12

Period 1 when compared to both music conditions, and that HR was lower during the slow-tempo 13

music condition during Recovery Period 2 when compared to fast-tempo music. Finally, HR was 14

lower during the fast-tempo music condition in Recovery Period 4 when compared to control (see 15

Figure 2 and Table 4). The main effect of condition was nonsignificant, F(2, 24) = .06, p = .945, ηp2 = 16

.01. 17

3.3.4. Oxygen uptake (% of V̇O2 max). Oxygen uptake was recorded continuously 18

throughout all exercise and recovery periods and was analyzed as a percentage of maximal aerobic 19

capacity. The condition x time interaction during exercise was nonsignificant, F(2.67, 32.02) = .29, p = 20

.812, ηp2 = .02. There were no main effects of condition, F(1.26, 15.14) = 1.09, p = .330, ηp

2 = .08, or 21

time, F(3, 36) = .39, p = .449, ηp2 = .03. Similarly, there was no condition x time interaction for the 22

recovery periods, F(8, 96) = .60, p = .776, ηp2 = .05, and no main effect of condition, F(1.28, 15.38) = 23

1.39, p = .267, ηp2 = .10, or time, F(4, 48) = 1.69, p = .168, ηp

2 = .12. 24

3.3.5. Minute ventilation (V̇E). There was no condition x time interaction during the exercise 25

bouts, F(3.04, 36.51) = .75, p = .608, ηp2 = .06, or a main effect of condition, F(2, 24) = .00, p = .997, 26

ηp2 = .00. During recovery periods, there was no significant condition x time interaction, F(8, 96) = 27

.90, p = .523, ηp2 = .07, or main effect of condition, F(2, 24) = 1.18, p = .324, ηp

2 = .09. 28


3.3.6. Tidal volume (VT). For measures taken during exercise, there was a nonsignificant 1

condition x time interaction, F(1.59, 19.10) = 1.70, p = .211, ηp2 = .12, and a nonsignificant main 2

effect of condition, F(2, 24) = .56, p = .583, ηp2 = .04. There was no condition x time interaction, F(8, 3

96) = .83, p = .583, ηp2 = .06, or main effect of condition, F(2, 24) = 2.08, p = .147, ηp

2 = .15, for 4

recovery period data. 5

3.3.7. Respiratory frequency (fR). Data collected during exercise indicated no condition x 6

time interaction, F(1.86, 22.37) = 1.25, p = .302, ηp2 = .10, and similarly, a nonsignificant main effect 7

of condition, F(2, 24) = .28, p = .756, ηp2 = .02. During recovery periods, there was no significant 8

condition x time interaction, F(3.53, 42.30) = .28, p = .870, ηp2 = .02, or main effect of condition, F(2, 9

24) = .42, p = .663, ηp2 = .03. 10

3.3.8. Respiratory duty cycle (TTOT). There was no significant condition x time interaction 11

during exercise bouts, F(1.51, 18.14) = .81, p = .569, ηp2 = .06. There was also no main effect of 12

condition, F(1.36, 16.65) = 1.36, p = .273, ηp2 = .10. During the recovery periods, there was no 13

significant condition x time interaction, F(8, 96) = .18, p = .994, ηp2 = .01, or main effect of condition, 14

F(2, 24) = 1.77, p = .193, ηp2 = .13. 15

3.4. Blood Lactate 16

There was no significant condition x time interaction, F(2, 24) = 1.12, p = .342, ηp2 = .09, and 17

no main effect of condition, F(2, 24) = .70, p = .509, ηp2 = .05. There was a significant main effect of 18

time, F(1, 12) = 28.22, p = .000, ηp2 = .70, indicating that post-exercise values were higher (M = 4.40 19

± .61) than baseline (M = 1.05 ± .09). 20

3.5. Tempo-Respiratory Entrainment 21

The condition x time interaction effect was nonsignificant (F[4, 48] = .58, p = .676, ηp2 = .05), 22

as were the main effects of condition and time (p > .05). 23

4. Discussion 24

The purpose of this study was to assess the influence of music on acute psychological and 25

cardiorespiratory recovery in between bouts of high-intensity exercise among trained participants. Our 26

research hypothesis was not supported given that fast-tempo music, rather than slow-tempo music, 27

positively influenced affective responses in all recovery periods when compared to a no-music control 28


condition. Furthermore, music does not appear to facilitate acute cardiorespiratory recovery in 1

between bouts of high-intensity treadmill exercise. 2

4.1. Affective Responses 3

Listening to fast-tempo, positively-valenced music (125-135 bpm) during the 3-min recovery 4

periods engendered a more pleasant experience when compared to a no-music control eliciting a FS 5

score of ~1 higher (p = .010; ηp2 = .38). This was a consistent finding across each of the five recovery 6

periods (see Figure 1), and was associated with a large effect size indicating a robust result. The 7

positive affective response to music is concordant with other exercise-related studies (e.g., Stork et al., 8

2015) and the efficacy of fast-tempo music in this instance could be associated with the HR range 9

recorded in the present study. A corpus of work has explored the relationship between exercise HR 10

and preference for music tempo (see Karageorghis & Jones, 2014). This work shows that, regardless 11

of exercise intensity (40–90% maxHRR), there is a preference for fast-tempo music during treadmill 12

exercise and cycle ergometry. These studies explored the application of in-task music (during 13

exercise) with working heart rates ranging from ~110 to ~180 b.min

-1 and participants in the present 14

study exhibited heart rates ranging from ~105 to ~180 b.min

-1 during recovery periods. It appears that 15

fast-tempo music elicits the most positive affective responses when heart rates are elevated, whether 16

this is during exercise or recovery periods. 17

The arousal reported by participants during the recovery periods increased significantly from 18

baseline (p = .006; FAS = 3.08 ± 0.17), but remained stable throughout recovery periods (FAS = 3.77 19

± 0.17 [Recovery Period 1]; 3.82 ± 0.23 [Recovery Period 2]; 3.87 ± 0.27 [Recovery Period 3]; 3.87 ± 20

0.29 [Recovery Period 4]; 3.56 ± 0.23 [Recovery Period 5]). Although the fast-tempo music selections 21

were rated as more highly-arousing than the slow-tempo tracks during the music selection process 22

(Stage 1), this was not reflected during the recovery periods. It appears that arousal increased 23

independently of the music administered and that the exercise was sufficient to significantly increase 24

arousal from baseline. The elevated arousal resulting from the intervals may have been sufficient for 25

participants to maintain an optimal arousal level for the session without any need for music to help in 26

regulating arousal. 27

4.2. Cardiorespiratory Responses 28


The significant interaction effect of condition x time for the HR recovery (p = .034, ηp2 = .16) 1

indicated that participants exhibited a lower HR at the end of the first recovery period during control, 2

and a lower HR during the second recovery period in the slow-tempo condition when compared to the 3

fast-tempo condition. Given that participants were engaged in prolonged exercise above the GET, 4

there was substantial cardiorespiratory drift, during which oxygen uptake and ventilation increased 5

progressively, as illustrated by the multiple main effects of time. Therefore, any music-moderated 6

effect on recovery HR would likely manifest in the early recovery periods. Despite the HR interactions 7

observed during recovery, there was no subsequent influence on exercise HR or associated 8

cardiorespiratory variables (see Table 3). This suggests that, in this population, lower HR during early 9

recovery periods is of limited physiological benefit in subsequent bouts of exercise. 10

4.3. Tempo-Respiratory Entrainment 11

Previous studies reported entrainment of breathing and music rhythms at rest (e.g., Haas et al., 12

1986; Bernadi et al., 2005), but the present study did not replicate these findings in an exercise 13

context. Despite Khalfa et al.’s (2008) suggestion that entrainment is a partially conscious process, 14

exercise ventilation is controlled by neural and humeral factors to enable the delivery of oxygen and 15

elimination of carbon dioxide (Forster et al., 2012). Consequently, it appears that when ventilation is 16

high, maintenance of homeostatic equilibrium will be the predominating factor in the control of 17

ventilation. During the first recovery period when ventilation was lowest, values were in excess of 18

three times those at rest (36.8 ± 10.7 vs. 11.2 ± 2.9 L.min

-1) and it seems as though such a high demand 19

restricts the likelihood of entrainment being manifest. The present results suggest that only resting 20

respiration would be susceptible to the subtle influence of music tempo on respiratory function. 21

The conscious and unconscious aspects of different types of entrainment may be a salient 22

factor (Phillips-Silver et al., 2010). Entrainment between musical tempo and HR is an unconscious 23

process, but entrainment between respiration rate and music tempo can be either conscious or 24

unconscious given that humans breathe without conscious cognitive control, but can also choose to 25

regulate breathing rate. From an information processing perspective, the notion of a limited attentional 26

capacity may be relevant when considering the capacity to process, and entrain with, external stimuli 27

such as music during periods of physical stress. Rejeski’s (1985) model of parallel processing 28


indicates that informational and emotional components are processed in parallel, rather than in 1

sequence. Furthermore, as exercise intensity increases, informational cues become stronger and 2

occupy the limited capacity of channels between preconscious and focal awareness. It might be that 3

during recovery from high-intensity exercise, internal informational cues predominate and there is 4

insufficient capacity remaining to process musical stimuli in order to consciously manipulate 5

respiration rate. 6

4.4 Technical Considerations 7

A high number of participants (n = 7) were unable to complete all of the testing sessions. We 8

applied an exercise intensity of ∆20-V̇O2 max, which is considered to be “heavy” exercise (Lansley et 9

al., 2011). This typifies an intensity at which athletes train for periods of ~3 min. The 5-min bout was 10

selected to allow for a relative steady-state in physiological responses, and the 3-min recovery period 11

to enable sufficient exposure to the musical stimuli (i.e., the musical stimuli would have long enough 12

to take effect). However, two participants were unable to tolerate the physical stress associated with 13

the extended interval duration. Future studies might seek to explore the role of music in promoting 14

recovery during alternative protocols such as the so-called practical model of low volume, high 15

intensity interval training (Little, Safdar, Wilkin, Tarnopolsky, & Gibala, 2010). The remaining five 16

participants withdrew owing to injury (n = 3) or competitive commitments (n = 2). 17

4.5. Practical Implications 18

The hypothesis that slow-tempo, positively-valenced music would promote the most positive 19

psychological state during recovery was based on previous suggestions (Terry & Karageorghis, 2011), 20

and findings that sedative music promotes effective psychological and physiological exercise recovery 21

(Jing & Xudong, 2008). There are some notable differences between previous work and the present 22

study that may explain the nature of our results. First, previous work has framed post-task, or 23

recuperative, music in the context of the final phase of an exercise session (i.e., no further bouts of 24

exercise within the session) but the present study sought to explore the utility of music as an aid to 25

recovery that took place in between repeated bouts of exercise. This is likely a seminal difference and 26

would suggest the need for terminological distinction. Accordingly, it is proposed that the term respite 27

music is adopted by researchers and practitioners to more accurately describe the application of music 28


during periods of recovery within an exercise session. The proposed term provides a useful 1

counterpoint to recuperative music, which refers to sedative music that is applied immediately after an 2

exercise or training session (Terry & Karageorghis, 2011). 3

The capacity for music to positively enhance the exercise experience has been demonstrated in 4

a number of studies (e.g., Hutchinson et al., 2011; Karageorghis & Jones, 2014). The present study 5

extends that work to suggest that fast-tempo, positively-valenced music can be used to afford an 6

effective respite that positively enhances the pleasure experienced during a high-intensity interval 7

session. The concept of “affective rebound” (Ekkekakis et al., 2008) demonstrates that affective 8

valence returns to pre-exercise levels almost immediately following cessation of exercise. Present data 9

indicate that pleasure can be enhanced beyond pre-exercise levels through the administration of fast-10

tempo, positively-valenced music during the rest periods of an interval running session in trained 11

participants. Furthermore, there are numerous studies reporting a link between acute affective 12

responses to exercise and subsequent adherence to exercise (see Rhodes & Kates, 2015 for a review); 13

interventions that can enhance acute affective responses in untrained populations warrant additional 14

investigation. 15

Given the typical affective responses during exercise, as depicted in the dual-mode model 16

(Ekkekakis, 2003), the high-intensity exercise bout itself will not typically result in positive affective 17

responses but the rest periods in-between exercise bouts offer an opportunity to ameliorate this 18

displeasure. Therefore, the use of fast-tempo, positively-valenced music appears to promote a more 19

pleasurable and thus tolerable exercise experience. 20

5. Conclusion 21

The present findings indicate that fast-tempo, positively-valenced music engenders positive 22

affective responses in the acute recovery phases of high-intensity interval training performed by 23

middle-distance runners. This finding is of relevance to coaches and practitioners working with 24

athletes and recreational exercisers, as it offers an easily implementable intervention by which to 25

increase the pleasure experienced during a physically demanding session. The findings are in accord 26

with other work indicating that music can enhance affective responses in a high-intensity exercise 27

context (e.g., Stork & Martin Ginis, 2016). The recorded physiological responses do not provide 28


robust evidence that slow or fast-tempo music expedites recovery in this context. Future research 1

might seek to examine the effects of music during the recovery periods following exercise performed 2

at lower intensities; specifically focusing on the extent to which music promotes respiratory 3

entrainment. A terminological distinction has been proposed herein to differentiate recuperative music 4

(applied post-task) from respite music (applied in-between bouts of exercise). Respite music has 5

pleasant–arousing qualities, in line with the activated state of the organism during a brief recovery 6

period, whereas recuperative music that is employed on cessation of exercise is characterized by 7

pleasant–relaxing qualities. 8


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19


Table 1 1

Music Tracks Administered in the Experimental Conditions 2

Track Title Artist(s) Year of

release

Official

bpm

Affect

Rating (M)

Arousal

Rating (M)

Slow tempo

At The River Groove Armada 1998 68 6.83 ± 1.47 2.83 ± 0.41

Can You Feel The Love Tonight Elton John 1994 67 6.33 ± 1.21 3.00 ± 1.10

I Wanna Be Yours Arctic Monkeys 2013 67 6.17 ± 1.94 3.50 ± 0.55

At Last Etta James 1960 56 6.07 ± 2.07 2.50 ± 0.55

All You Ever Wanted The Black Keys 2008 59 6.50 ± 1.64 3.33 ± 0.82

Fast tempo

Old Yellow Bricks Arctic Monkeys 2007 135 7.00 ± 1.10 6.67 ± 0.82

Satisfaction Rolling Stones 1965 136 6.67 ± 0.82 7.67 ± 1.03

Hideaway Kiesza 2014 123 6.33 ± 1.03 6.67 ± 0.82

What Is Love Haddaway 1993 124 6.67 ± 1.75 7.67 ± 0.52

Fever The Black Keys 2014 128 6.17 ± 1.47 6.83 ± 0.98

3

4

5


Table 2 1

Peak Physiological Responses to Incremental Treadmill Running, mean ± SD (N = 13) 2

3

4

5

6

7

8

9

10

11

Note. V̇O2, O2 uptake; V̇CO2, CO2 output; RER, respiratory exchange ratio; HR, heart rate; V̇E, 12

minute ventilation; VT, tidal volume; fR, respiratory frequency; TTOT, respiratory duty cycle; RPECR10, 13

rating of perceived exertion. 14

Variables Rest Max

Treadmill Speed (km

.hr

-1) 0 ± 0 20 ± 2

V̇O2 (L·min-1

) 0.38 ± 0.09 4.34 ± 0.50

V̇O2 (ml·kg·min-1

) 5.4 ± 1.1 61.6 ± 6.1

V̇CO2 (L·min-1

) 0.36 ± 0.09 5.12 ± 0.53

RER 0.95 ± 0.13 1.18 ± 0.07

HR (b·min-1

) 57 ± 9 196 ± 7

V̇E (L·min-1

) 11.7 ± 2.9 155 ± 20.8

VT (L) 0.84 ± 0.24 2.74 ± 0.38

fR (br·min-1

) 14.6 ± 2.9 58.7 ± 10.1

TTOT (s) 4.4 ± 1.1 1.0 ± 0.2

RPECR10 0 ± 0 10 ± 1


Table 3

Descriptive Statistics for all Dependent Variables Recorded during Exercise Bouts (M ± SD)

Note. V̇O2, O2 uptake; V̇CO2, CO2 output; HR, heart rate; V̇E, minute ventilation; VT, tidal volume; fR, respiratory frequency; TTOT, respiratory duty cycle;

RPECR10, rating of perceived exertion. a = significant condition x time interaction,

b = significant main effect of condition,

c = significant main effect of time.

EFFORT 1 EFFORT 2 EFFORT 3 EFFORT 4 EFFORT 5

Slow Fast Control Slow Fast Control Slow Fast Control Slow Fast Control Slow Fast Control

V̇O2 (L

.min

-1) 3.37

± 5.56

3.39

± 5.26

3.22

± 6.91

3.27

± 5.64

3.32

± 5.26

3.13

± 6.38

3.27

± 5.92

3.32

± 5.59

3.12

± 7.00

3.30

± 5.78

3.33

± 5.56

3.16

± 5.80

3.31

± 6.03

3.30

± 5.80

3.14

± 5.31

V̇O2 (%max)

78

± 10

79

± 12

74

± 12

76

± 11

77

± 13

72

± 12

76

± 12

77

± 13

72

± 13

76

± 11

77

± 13

73

± 11

76

± 12

77

± 14

73

± 10

V̇CO2 (L

.min

-1)

3.37

± 5.64

3.41

± 5.80

3.34

± 7.22

3.16

± 5.68

3.20

± 5.64

3.12

± 6.15

3.12

± 6.00

3.19

± 5.93

3.09

± 6.65

3.16

± 5.84

3.19

± 5.92

3.12

± 5.81

3.15

± 6.13

3.15

± 6.21

3.09

± 5.69

HR (b

.min

-1) c

171.50

± 6.97

171.38

± 5.85

171.85

± 9.27

175.46

± 7.99

175.15

± 6.91

175.46

± 9.66

179.54

± 7.73

178.69

± 6.50

179.08

± 10.02

181.00

± 8.24

181.08

± 6.59

181.46

± 9.88

183.00

± 8.05

182.08

± 7.24

182.92

± 9.17

V̇E (L

.min

-1) c

94.13

± 25.38

93.38

± 24.67

93.87

± 22.93

91.84

± 24.59

93.93

± 21.41

93.96

± 21.45

96.65

± 25.13

95.99

± 24.28

96.48

± 22.21

98.77

± 25.85

98.14

± 24.73

98.04

± 21.39

99.79

± 26.18

99.51

± 25.21

99.04

± 23.00

VT (L

.min

-1) c

2.41

± 0.32

2.48

± 0.29

2.43

± 0.26

2.25

± 0.35

2.17

± 0.26

2.25

± 0.29

2.17

± 0.30

2.21

± 0.29

2.23

± 0.29

2.14

± 0.30

2.19

± 0.30

2.08

± 0.24

2.13

± 0.28

2.16

± 0.29

2.03

± 0.27

fR (br

.min

-1) c

39.17

± 9.36

37.83

± 8.96

38.71

± 8.31

41.11

± 10.24

43.10

± 6.56

42.09

± 8.90

44.73

± 10.00

43.56

± 9.52

43.71

± 9.32

46.65

± 11.50

44.97

± 9.66

47.10

± 7.93

47.16

± 11.89

46.48

± 10.59

48.60

± 8.40

TTOT (s)

c

1.67

± 0.50

1.64

± 0.48

1.69

± 0.45

1.60

± 0.50

1.39

± 0.25

1.56

± 0.46

1.48

± 0.47

1.42

± 0.51

1.49

± 0.45

1.43

± 0.50

1.38

± 0.52

1.35

± 0.27

1.42

± 0.49

1.35

± 0.54

1.30

± 0.25

RPECR10

c

4.77

± 1.09

4.69

± 1.25

4.69

± 1.18

4.77

± 1.17

5.15

± 1.41

5.08

± 1.32

5.38

± 1.39

5.62

± 1.45

5.31

± 1.38

5.77

± 1.36

5.77

± 1.48

5.85

± 1.41

5.85

± 1.34

6.08

± 1.80

6.23

± 1.54


Table 4

Descriptive Statistics for all Dependent Variables Recorded during Recovery Periods (M ± SD)

Note. V̇O2, O2 uptake; V̇CO2, CO2 output; HR, heart rate; V̇E, minute ventilation; VT, tidal volume; fR, respiratory frequency; TTOT, respiratory duty cycle;

ENT, proportion of respite time spent entrained; FS, Feeling Scale; FAS, Felt Arousal Scale. a = significant condition x time interaction,

b = significant main

effect of condition, c = significant main effect of time.

RECOVERY 1 RECOVERY 2 RECOVERY 3 RECOVERY 4 RECOVERY 5

Slow Fast Control Slow Fast Control Slow Fast Control Slow Fast Control Slow Fast Control

V̇O2 (L.min-1) 1.06

± 0.25

1.10

± 0.24

0.99

± 0.32

1.09

± 0.27

1.11

± 0.27

1.00

± 0.34

1.06

± 0.36

1.11

± 0.27

1.03

± 0.34

1.09

± 0.30

1.16

± 0.33

1.03

± 0.31

1.11

± 0.30

1.11

± 0.29

1.02

± 0.31

V̇CO2 (L

.min

-1) 1.18

± 0.30

1.23

± 0.30

1.16

± 0.40

1.18

± 0.33

1.19

± 0.32

1.13

± 0.41

1.13

± 0.43

1.19

± 0.31

1.15

± 0.43

1.16

± 0.35

1.23

± 0.36

1.15

± 0.46

1.17

± 0.35

1.19

± 0.34

1.14

± 0.42

HR (b

.min

-1) a, c

107.00

± 8.74

106.69

± 6.38

104.31

± 10.42

110.92

± 7.57

114.15

± 8.13

112.85

± 12.19

119.08

± 8.54

120.54

± 8.18

120.92

± 12.47

125.77

± 12.90

124.31

± 9.52

126.92

± 13.02

129.31

± 11.21

128.38

± 9.67

127.77

± 12.75

V̇E (L

.min

-1) c

36.15

± 10.57

37.92

± 11.34

36.30

± 11.08

36.74

± 11.49

38.54

± 11.66

37.98

± 11.08

36.60

± 12.64

40.05

± 12.31

39.74

± 12.95

38.92

± 12.10

41.44

± 12.70

40.48

± 14.63

39.68

± 11.87

41.27

± 12.60

41.84

± 15.01

VT (L

.min

-1) c

1.36

± 0.29

1.40

± 0.22

1.40

± 0.23

1.31

± 0.27

1.34

± 0.24

1.35

± 0.28

1.25

± 0.25

1.31

± 0.22

1.37

± 0.27

1.29

± 0.25

1.34

± 0.27

1.31

± 0.25

1.25

± 0.23

1.26

± 0.25

1.33

± 0.24

fR (br

.min

-1) c

26.55

± 5.39

27.11

± 5.86

26.19

± 6.91

28.37

± 29.37

29.37

± 8.66

29.10

± 6.91

29.26

± 7.62

30.81

± 7.99

29.74

± 9.75

30.73

± 8.91

31.65

± 9.01

31.47

± 11.37

32.26

± 9.58

33.15

± 9.04

32.28

± 11.99

TTOT (s)

c 2.54

± 0.60

2.34

± 0.58

2.59

± 0.78

2.44

± 0.74

2.32

± 0.95

2.48

± 0.91

2.39

± 0.74

2.23

± 0.91

2.39

± 0.84

2.30

± 0.76

2.17

± 0.87

2.29

± 0.75

2.22

± 0.81

2.03

± 0.72

2.30

± 0.91

ENT (%) 20.77

± 15.53

19.23

± 10.38

- 20.00

± 12.25

20.00

± 12.25

- 17.69

± 12.35

20.77

± 10.38

- 26.15

± 13.87

26.15

± 17.10

- 24.62

± 13.30

16.92

± 13.77

-

FS

b 2.08

± 1.19

2.54

± 1.05

1.46

± 1.51

2.08

± 1.19

2.54

± 0.88

1.54

± 0.97

2.08

± 1.50

2.46

± 0.97

1.54

± 1.20

2.0

± 1.35

2.54

± 1.71

1.62

± 1.12

2.08

± 1.55

2.69

± 1.49

1.69

± 1.75

FAS

c 3.46

± 0.97

4.15

± 0.69

3.69

± 0.75

3.69

± 1.18

4.00

± 0.71

3.77

± 1.09

3.92

± 1.26

3.85

± 1.07

3.85

± 0.99

3.54

± 1.27

4.15

± 1.14

3.92

± 1.12

3.54

± 1.33

3.92

± 0.86

3.23

± 1.36


Fig. 1. Significant main effect of condition for Feeling Scale scores. *p = .010; fast-tempo music >

control condition.


Fig. 2. Significant condition x time interaction effect for heart rate during recovery (p = .034). *

control condition < slow- and fast-tempo condition, ** slow-tempo < fast-tempo, *** fast-tempo <

control condition.

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